Abstract
A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing) > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions. This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Simulated data allowed us to reject the hypothesis that stochastic processes were responsible for community assembly, suggesting that niche effects prevailed. Consistent with this idea we identified six distinct community classes that contained samples collected from distant locations. Structural equation models showed there was a functional signature associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions (PiCRUST). This approach allowed us to show that the classes contained distinct genetic repertoires reflecting community-level ecological strategies. The ecological strategies resemble the classical distinction between r- and K-strategists, suggesting that bacterial community assembly may be explained by simple ecological mechanisms.
Highlights
A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units
We analysed 753 bacterial communities sampled from water-filled beech tree-holes in the southwest of the UK32
We suggest that the high ANOSIM statistics we observed require unrealistic levels of dispersal for the pattern to be explained by stochastic processes alone (Supplementary Fig. 29), and points towards a hypothesis that similar environmental conditions occur at distant locations
Summary
A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing) > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Microbes inhabitating a host sometimes have a substantial impact on host performance, for example, turning a healthy into a diseased host[11] Such extreme impacts of individual taxa make it relatively simple to infer a direct link between community composition and function. An important step forward comes from manipulative experiments in natural environments, which have identified variables such as pH12, salinity[8], sources of energy[13], the number of species[14] and environmental complexity[4] as key players in the relationship between bacterial community structure and functioning
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